D2D communications in 5G mobile cellular networks : we propose and validate a novel approach to mobility management

University of Technology Sydney. Faculty of Engineering and Information Technology.Fifth Generation (5G) stands for future fitness combined with flexible technical solutions that combine with the latest wireless technology. 5G is expected to multiply a thousand times (1000x) in data speed with 20.4 billion devices (IoT) connected to the network by 2020. This literally means everything connecting to everything. From the network point of view, lower latency along with high flexibility is not limited just to 5G. It is already being implemented in real networks. The number of wireless devices connected to networks has increased remarkably over the last couple of decades. Ubiquitous voice and data connections are the fundamental requirements for the next generation of wireless technology. Device-to-Device communication is widely known as D2D. It is a new paradigm for cellular communication. It was initially proposed to boost network performance. It is considered to be an integral part of the next generation (5G) of telecommunications networks. It takes place when two devices communicate directly without significant help from the base station. In a cellular network, Device-to-Device communication has been viewed as a promising technology overcoming many existing problems. These include capacity, quality and scarce spectrum resources. However, this comes at the price of increased interference and complex mobility issues, even though it was proposed as a new paradigm to enhance network performance. Nevertheless, it is still a challenge to manage devices that are moving. Cellular devices without well-managed mobility are hardly acceptable. Considering in-band underlay D2D communication, a well-managed mobility system in cellular communication should have lower latency, lower power consumption and higher data rates. In this dissertation, we review existing mobility management systems for LTE-Advanced technology and propose an algorithm to be used over the current system so that lower signalling overheads and less delay, along with uninterrupted D2D communication, are guaranteed. We model and simulate our algorithm, comparing the results with mathematical models based on Markov theory. As in other similar communication systems, mobility management for D2D communication is yet to be explored fully. There are few research papers published so far. What we can say is that the intention of such systems in cellular networks are to enable lower latency, lower power consumption, less complexity and, last but not least, uninterrupted data connections. Our simulation results validate our proposed model and highlight D2D communication and its mobility issues. An essential element of our proposal is to estimate the user’s location. We can say that a mobility management system for D2D communication is hardly workable if the location of the users is not realisable. This dissertation also shows some latest techniques for estimating the direction of arrival (DOA) with mathematical models and simulation results. Smart antenna systems are proposed. It is possible to determine the location of a user by considering the uplink transmission system. Estimating the channel and actual path delay is also an important task, which might be done by using 1D uniform linear array (ULA) or 2D Uniform Rectangular (URA) array antenna systems. In this chapter, 1D ULA is described utilising some well-known techniques. The channel characteristics largely determine the performance of an end-to-end communication system. It determines the signal transformation while propagating through the channel between receivers and transmitters. Accurate channel information is crucial for both the transmitter and receiver ends to perform at their best. The ultimate focus of this part is to estimate the channel based on 2D parameter estimation. Uniform Rectangular Array (URA) is used to perform the 2D parameter estimation. It is possible to estimate azimuth and elevation of a source by using the URA model. The problem of mobility in this context has been investigated in few papers, with no reliable solutions as yet. We propose a unique algorithm for mobility management for D2D communications. In this dissertation, we highlight and explain the mobility model mathematically and analytically, along with the simulation of the Markovian model. A Markov model is essentially a simplified approach to describing a system that occupies a discrete state at any point in time. We also make a bridge between our mobility algorithm and a Markovian model

Spatial Parameter Identification for MIMO Systems in the Presence of Non-Gaussian Interference

Reliable identification of spatial parameters for multiple-input multiple-output (MIMO) systems, such as the number of transmit antennas (NTA) and the direction of arrival (DOA), is a prerequisite for MIMO signal separation and detection. Most existing parameter estimation methods for MIMO systems only consider a single parameter in Gaussian noise. This paper develops a reliable identification scheme based on generalized multi-antenna time-frequency distribution (GMTFD) for MIMO systems with non-Gaussian interference and Gaussian noise. First, a new generalized correlation matrix is introduced to construct a generalized MTFD matrix. Then, the covariance matrix based on time-frequency distribution (CM-TF) is characterized by using the diagonal entries from the auto-source signal components and the non-diagonal entries from the cross-source signal components in the generalized MTFD matrix. Finally, by making use of the CM-TF, the Gerschgorin disk criterion is modified to estimate NTA, and the multiple signal classification (MUSIC) is exploited to estimate DOA for MIMO system. Simulation results indicate that the proposed scheme based on GMTFD has good robustness to non-Gaussian interference without prior information and that it can achieve high estimation accuracy and resolution at low and medium signal-to-noise ratios (SNRs)

Performance Analysis of Angle of Arrival Algorithms Applied to Radiofrequency Interference Direction Finding

Radiofrequency (RF) interference threatens the functionality of systems that increasingly underpin the daily function of modern society. In recent years there have been multiple incidents of intentional RF spectrum denial using terrestrial interference sources. Because RF based systems are used in safety-of-life applications in both military and civilian contexts, there is need for systems that can quickly locate these interference sources. In order to meet this need, the Air Force Research Laboratory Weapons Directorate is sponsoring the following research to support systems that will be able to quickly geolocate RF interferers using passive angle-of-arrival estimation to triangulate interference sources. This research studies the performance of angle-of arrival (AoA) estimation algorithms for an existing uniform linear antenna array. Four algorithms are presented, they are phase-shift beamforming, Capon or Minimum Variance Distortionless Response (MVDR) beamforming, the Multiple Signal Identification and Classification (MUSIC) algorithm, and one instantiation of a Maximum Likelihood Estimation (MLE) algorithm. A modeling and simulation environment using MATLAB™ is developed and the performance of each algorithm is simulated as implemented on a uniform linear array. Performance is characterized under various non-ideal conditions

Integrated Sensing and Communication Signals Toward 5G-A and 6G: A Survey

Integrated sensing and communication (ISAC) has the advantages of efficient spectrum utilization and low hardware cost. It is promising to be implemented in the fifth-generation-advanced (5G-A) and sixth-generation (6G) mobile communication systems, having the potential to be applied in intelligent applications requiring both communication and high-accurate sensing capabilities. As the fundamental technology of ISAC, ISAC signal directly impacts the performance of sensing and communication. This article systematically reviews the literature on ISAC signals from the perspective of mobile communication systems, including ISAC signal design, ISAC signal processing algorithms and ISAC signal optimization. We first review the ISAC signal design based on 5G, 5G-A and 6G mobile communication systems. Then, radar signal processing methods are reviewed for ISAC signals, mainly including the channel information matrix method, spectrum lines estimator method and super resolution method. In terms of signal optimization, we summarize peak-to-average power ratio (PAPR) optimization, interference management, and adaptive signal optimization for ISAC signals. This article may provide the guidelines for the research of ISAC signals in 5G-A and 6G mobile communication systems.Comment: 25 pages, 13 figures, 8 tables. IEEE Internet of Things Journal, 202

Development of a Resource Manager Framework for Adaptive Beamformer Selection

Adaptive digital beamforming (DBF) algorithms are designed to mitigate the effects of interference and noise in the electromagnetic (EM) environment encountered by modern electronic support (ES) receivers. Traditionally, an ES receiver employs a single adaptive DBF algorithm that is part of the design of the receiver system. While the traditional form of receiver implementation is effective in many scenarios it has inherent limitations. This dissertation proposes a new ES receiver framework capable of overcoming the limitations of traditional ES receivers. The proposed receiver framework is capable of forming multiple, independent, simultaneous adaptive digital beams toward multiple signals of interest in an electromagnetic environment. The main contribution of the research is the development, validation, and verification of a resource manager (RM) algorithm. The RM estimates a set of parameters that characterizes the electromagnetic environment and selects an adaptive digital beam forming DBF algorithm for implementation toward all each signal of interest (SOI) in the environment. Adaptive DBF algorithms are chosen by the RM based upon their signal to interference plus noise ratio (SINR) improvement ratio and their computational complexity. The proposed receiver framework is demonstrated to correctly estimate the desired electromagnetic parameters and select an adaptive DBF from the LUT

Practical Secrecy at the Physical Layer: Key Extraction Methods with Applications in Cognitive Radio

The broadcast nature of wireless communication imposes the risk of information leakage to adversarial or unauthorized receivers. Therefore, information security between intended users remains a challenging issue. Currently, wireless security relies on cryptographic techniques and protocols that lie at the upper layers of the wireless network. One main drawback of these existing techniques is the necessity of a complex key management scheme in the case of symmetric ciphers and high computational complexity in the case of asymmetric ciphers. On the other hand, physical layer security has attracted significant interest from the research community due to its potential to generate information-theoretic secure keys. In addition, since the vast majority of physical layer security techniques exploit the inherent randomness of the communication channel, key exchange is no longer mandatory. However, additive white Gaussian noise, interference, channel estimation errors and the fact that communicating transceivers employ different radio frequency (RF) chains are among the reasons that limit utilization of secret key generation (SKG) algorithms to high signal to noise ratio levels. The scope of this dissertation is to design novel secret key generation algorithms to overcome this main drawback. In particular, we design a channel based SKG algorithm that increases the dynamic range of the key generation system. In addition, we design an algorithm that exploits angle of arrival (AoA) as a common source of randomness to generate the secret key. Existing AoA estimation systems either have high hardware and computation complexities or low performance, which hinder their incorporation within the context of SKG. To overcome this challenge, we design a novel high performance yet simple and efficient AoA estimation system that fits the objective of collecting sequences of AoAs for SKG. Cognitive radio networks (CRNs) are designed to increase spectrum usage efficiency by allowing secondary users (SUs) to exploit spectrum slots that are unused by the spectrum owners, i.e., primary users (PUs). Hence, spectrum sensing (SS) is essential in any CRN. CRNs can work both in opportunistic (interweaved) as well as overlay and/or underlay (limited interference) fashions. CRNs typically operate at low SNR levels, particularly, to support overlay/underlay operations. Similar to other wireless networks, CRNs are susceptible to various physical layer security attacks including spectrum sensing data falsification and eavesdropping. In addition to the generalized SKG methods provided in this thesis and due to the peculiarity of CRNs, we further provide a specific method of SKG for CRNs. After studying, developing and implementing several SS techniques, we design an SKG algorithm that exploits SS data. Our algorithm does not interrupt the SS operation and does not require additional time to generate the secret key. Therefore, it is suitable for CRNs